This application relates generally to automobile technology and more particularly to warning systems in vehicles.
Vehicle spinout detection is a safety feature designed to determine whether the vehicle has spun out of control, which becomes especially important during low visibility weather conditions. Robust calculation of the vehicle's lateral velocity (or side slip angle) is important for spinout detection systems. During spinout events, lateral velocity is necessary to detect an unstable vehicle, which may have normal yaw rates. Also in these events, the longitudinal vehicle velocity cannot be accurately measured by wheel speed because of excessive wheel slip. Therefore, a successful spinout detection system must involve an accurate determination of the vehicle lateral and longitudinal velocities. Although it is possible to measure vehicle velocities directly by using dedicated measuring devices such as optical sensors and GPS, there exist practical issues such as cost, accuracy, and reliability that prevent the use of such devices on vehicles.
Lateral velocity calculation algorithms implemented on vehicles for vehicle spinout detection are normally based on sensors and generally involve mathematical integration of lateral acceleration and other related variables. Such calculation, however, introduces errors over time due to integration and the inability to measure lateral acceleration directly. These errors can be so substantial that the calculation and subsequent spinout detection is compromised.
It would be highly desirable to develop a cost-effective strategy for improved discrimination between vehicle spinout and non-spinout events by utilizing already-available signals in vehicles, without adding additional hardware.